This invention relates to the detection of clear air turbulence, vertical windshear and wake vortices; and more particularly, to systems for alerting pilots to the presence of these hazards.
Clear air turbulence (CAT) and wake vortices present potential hazards to aircraft in flight. An aircraft passing through such phenomenon may experience an upset from steady, equilibrium flight. This upset may be severe enough to cause injury to passengers or in severe cases may cause a departure from controlled flight. CAT is a weather phenomenon that is due to vertical wind shear in the atmosphere and usually occurs in temperature inversion layers typically found in the tropopause.
Clear air turbulence has been identified by airlines, FAA, and NTSB as the leading cause of aviation injuries, costing major airlines at least $100 million per year. It is usually caused by convective storms, mountain waves, or jet stream activities. Currently, there is no adequate means to predict turbulence early enough to allow the pilot to avoid it and minimize its impact.
Since the conditions that result in clear air turbulence are not visually apparent nor are they generally detectable by active sensors such as radar, there have been a number of attempts to detect wind shear and clear air turbulence conditions by passive detectors. In particular, attempts have been made to sense air temperature gradients, which are associated with air turbulence, by detecting the radiation emanating from the atmosphere ahead of the aircraft in the infrared and microwave spectral regions. The intensity of the detected radiation varies with the atmospheric temperatures along the line of sight of the detector. Typically these passive systems use a radiometer to measure the thermal radiation from one of the atmospheric gases such as carbon dioxide (CO2), oxygen (O2) or water vapor (H2O) to determine changes in the spatial temperature profile in front of the aircraft. Examples of such approaches based on the infrared emission of CO2 are provided in U.S. Pat. Nos. 3,475,963, 3,735,136, 3,780,293, 3,935,460, 4,266,130, 4,427,306, 4,937,447, 4,965,572, 4,965,573, 5,105,191, 5,276,326 and 5,285,070. Other approaches determine atmospheric temperature by measuring the microwave emission from O2 as described in U.S. Pat. Nos. 3,359,557, 3,380,055, 4,346,595 and 5,117,689.
Systems for measuring atmospheric temperature based on infrared emission from H2O are described in U.S. Pat. No. 4,266,130 and in the paper by Kuhn et al, xe2x80x9cClear Air Turbulence: Detection by Infrared Observations of Water Vaporxe2x80x9d in Science, Vol. 196, p.1099, (1977). In addition, there have been several papers written describing these types of passive infrared systems including: S. M. Norman and N. H. Macoy, xe2x80x9cRemote Detection of Clear Air Turbulence by Means of an Airborne Infrared System,xe2x80x9d AIAA Paper No. 65-459 presented at the AIAA Second Annual Meeting, San Francisco, CA, July 26-29, 1965; and R. W. Astheimer, xe2x80x9cThe Remote Detection of Clear Air Turbulence by Infrared Radiationxe2x80x9d in Applied Optics Vol. 9, No. 8, p.1789 (1970). In U.S. Pat. No. 4,346,595, Gary describes a microwave radiometer for determining air temperatures in the atmosphere at ranges of about 3 km from the aircraft for the purpose of detecting the height of the tropopause and the presence of temperature inversions. He teaches that by flying the aircraft above or below the tropopause or temperature inversion layer, it is possible to avoid CAT. Since the effective range of the microwave radiometer is relatively short, the system doesn""t provide sufficient warning time for the aircraft to avoid the CAT condition. The present invention has detection ranges on the order of 100 km which will allow time for the aircraft to change altitude to avoid CAT.
A number of the above systems were not successful or were only partially successful because they were based solely on the measurement of atmospheric temperature in order to predict the presence of turbulence. A more reliable indication of atmospheric turbulence can be realized by determining the Richardson number, Ri. The use of the Richardson number to determine the stability of the atmosphere is well known in meteorology (see, for example, D. Djuric, xe2x80x9cWeather Analysis,xe2x80x9d Prentice Hall, Englewood Cliffs, N.J., 1994, p. 64). In U.S. Pat. No. 5,117,689, Gary discussed the correlation of the reciprocal of the Richardson number with the occurrence of CAT conditions. The Richardson number, Ri, contains two components: (1) the vertical lapse rate of potential temperature and (2) the wind shear which is related to the horizontal temperature gradient. A number of the prior art discussions measure the vertical temperature lapse rate. Gary used the inertial navigation system (INS) to measure the East-West and North-South components of the wind (the wind shear) along with a microwave radiometer to measure the air temperature vertical lapse rate. This information is then used to calculate the Richardson number or its reciprocal. The deficiency of the system described in this patent (U.S. Pat. No. 5,117,689) is that it determines the Richardson number at relatively close ranges (less than 3 km) and therefore does not provide advance warning of the CAT condition and that it measures the wind shear only at the aircraft.
Previous approaches for the determination of the range and probability of CAT can be summarized as follows:
U.S. Pat. No. 5,276,326 to Philpott determines turbulence as a function of temperature vs. range through the analysis of infrared radiometer signals at two or more discrete wavelengths. The temperature associated with a given range as a function of wavelength is then derived through a matrix inversion process. This transition is difficult and requires noise and error free input data to yield valid results. Gary overcomes the multiple wavelength difficulty in U.S. Pat. No. 4,346,595 by measuring effective temperature and range at a single wavelength, however no attempt is made to determine the probability of clear air turbulence using the Richardson number (Ri). In U.S. Pat. No. 5,117,689, Gary teaches the significance of the Richardson number in CAT prediction but does not suggest a method to derive Ri directly from radiometric measurements of horizontal and vertical temperature lapse rates obtained by combining azimuth and elevation scanning with the aircraft motion to produce a temperature map.
The above methods for airborne detection of clear air turbulence require the use of an aircraft sensor. Both infrared and radar sensors have been suggested for use. The practical difficulties involved with implementing these systems are several. First, the extremely small changes in temperature associated with the rising air current must be detected by those systems using infrared sensing. This task can be difficult to accomplish in thermally noisy environments or at long range. Second, such infrared systems require a clear lens to protect the infrared sensor. Real world flight conditions make the protection and maintenance of the lens such that reliable readings could be had costly and difficult. Third, those systems employing radar must have either a dedicated radar or must employ existing aircraft radar originally designed and dedicated for other purposes. Dedicated radar systems, such as LIDAR, tend to be extremely heavy which imposes fuel and capacity costs on the aircraft operator. The operator also must shoulder the additional burden of acquiring and maintaining a separate radar system. Fourth, the sensor is required to sweep out a large expanse of area in to either side of the aircraft and at various ranges in front of the aircraft. This requirement means that the sensor and the associated signal processing system must acquire and analyze a large quantity of data. Detecting the subtle changes indicative of turbulence becomes more difficult at long range. Furthermore, the bandwidth and time dedicated to the sensing activity can become onerous when the sensor is shared with other tasks, or when rapid update rates are desired.
Other solutions for avoiding invisible flight hazards such as CAT involve the use of mathematical atmospheric models. In particular, wake vortices models have been promulgated for several aircraft types. Air traffic controllers in the United States employ these models to develop separation rules such that one aircraft""s vortices do not pose a hazard to others. One such model used by controllers is called AVOSS, or Aircraft Vortex Separation System. Such models do not actually detect the presence of vortices or turbulence, but merely indicated theoretical behaviors and regions of likely occurrence.
As discussed herein, radar data alone is usually insufficient to give accurate nowcast of turbulence. Some meteorological data useful for either developing or refining a turbulence nowcast can only be obtained through uplinking data from a ground-based information source via a data link. However, the limited bandwidth of the data link means that very little of the possible gigabytes of storm data available from ground sources are able to be uplinked to the aircraft. This embodiment of the invention overcomes the difficulties associated with uplinking ground-based storm data by applying observational data to short-term prediction algorithms. This embodiment of the invention is a method for determining a nowcast of aviation turbulence without utilizing other meteorological data to supplement radar data. Preferably, the method of this invention utilizes data input from airborne weather radar and onboard thermal sensors to predict convection induced turbulence (CIT).
According to the present invention, observational data and short-term prediction algorithms are combined to provide a turbulence nowcast that estimates the probability, intensity, and location of turbulence with an adequate lead-time that allows the pilot to react by avoiding the dangerous area completely or choosing the best route to minimize the impact of turbulence encounter.
According to one aspect of the invention, an airborne convection induced turbulence nowcast system includes an on-board memory for storing a signal representative of a radar power return from a weather condition; and an on-board processor coupled to the memory. The processor is a computer adapted to process said radar power return data to provide spatial and temporal weather condition information, determine physical parameters of the weather condition as a function of the spatial and temporal whether condition information, and process the physical parameters as a function of predetermined diagnostic parameters to determine turbulence information and generate a nowcast of convection induced turbulence.
According to various aspects of the invention, the physical parameters are preferably one or more of a maximum upward G-factor, a maximum downward G-factor, a minimum moment of inertia of the radar reflectivity, a maximum moment of inertia of the radar reflectivity, a ratio of the minimum and maximum moments,of inertia, a vertical velocity of wind, a mean reflectivity of an upwind area, a mean reflectivity of a downwind area, and a ratio between the mean reflectivity of upwind and downwind areas. The maximum radar reflectivity and the first moment of the radar reflectivity are additional physical storm parameters for use with the nowcast algorithm to predict the locations of convection induced turbulence.
According to other aspects of the invention, the diagnostic parameters include one or more of a pattern of the weather condition, an extent of the weather condition, an intensity of the weather condition, maturity of the weather condition, and a motion of the weather condition.
According to various aspects of the invention, the processor of the airborne convection induced turbulence nowcast system is further adapted to determine a turbulence index as a function of the turbulence information; and the nowcast is further generated as a function of turbulence index. The on-board memory of the nowcast system also stores convection induced turbulence information as a function of predetermined weather condition features. The processor is further adapted to extract features from the radar power return signal corresponding to the predetermined weather condition features, and retrieve from the on-board memory the convection induced turbulence information corresponding to the extracted features.
According other aspects of the invention, the turbulence index is a weighted and normalized summation of various combinations of the diagnostic parameters.
According to various other aspects of the invention, the processor of the nowcast system of the invention is further coupled to receive a signal representative of additional meteorological data, and the processor is further adapted to process the additional meteorological data in combination with the turbulence information to generate the nowcast of convection induced turbulence. Furthermore, the additional meteorological data are preferably data that indicates at least one or more of the severity of the weather condition, the current developmental stage of the weather condition, and the type of weather condition under consideration. The additional meteorological data optionally include lightning data.
The present invention also includes the methods implemented by the convection induced turbulence nowcast system of the invention and various aspects thereof.
According to yet other aspects of the invention, the present invention provides a novel method for processing radar return data to determine the storm center and horizontal wind direction at aircraft cruise altitudes, thereby defining the probable location of the turbulence existing outside of significant radar reflectivity area.
According to various aspects of the invention, the nowcast method of the invention determines the center of mass and minimum moment of inertia of radar reflectivity of the storm. The radar reflectivity area is divided into upwind and downwind areas by a line passing through the storm center of mass perpendicular to the axis of minimum moment of inertia. The mean radar reflectivity of each area is computed. The horizontal wind direction is determined using the criteria that the area with larger mean radar reflectivity is the upperwind portion and the other area with smaller mean value is the downwind portion. This horizontal wind information is supplied to the nowcast algorithm of the invention, preferably in combination with information describing the type of storm encountered, to determine the location, the probability, location, and intensity of turbulence.